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Full-Text Articles in Bioinformatics

Annotation Of Non-Model Species’ Genomes, Taiya Jarva Jul 2023

Annotation Of Non-Model Species’ Genomes, Taiya Jarva

Master's Theses

The innovations in high throughput sequencing technologies in recent decades has allowed unprecedented examination and characterization of the genetic make-up of both model and non-model species, which has led to a surge in the use of genomics in fields which were previously considered unfeasible. These advances have greatly expanded the realm of possibilities in the fields of ecology and conservation. It is now possible to the identification of large cohorts of genetic markers, including single nucleotide polymorphisms (SNPs) and larger structural variants, as well as signatures of selection and local adaptation. Markers can be used to identify species, define population …


Polycyclic Aromatic Hydrocarbons And The Microbiomes Of Two Benthic Species, Samantha Ells Aug 2021

Polycyclic Aromatic Hydrocarbons And The Microbiomes Of Two Benthic Species, Samantha Ells

Master's Theses

The presence of oil has been shown to affect the microbiomes of the water column, sediments, and organisms, both by altering the diversity and the composition of those microbial communities. If the microbiome is altered it may no longer provide benefits to its host organism, impacting its ability to survive. Thus, it is important to understand the effects of large-scale contamination events including the Deepwater Horizon oil spill. This study set out to examine the effects of oil exposure on the microbiome of two benthic species, southern flounder (Paralichthys lethostigma) and eastern oysters (Crassostrea virginica) to further understand the effects …


The Antimicrobial Activity And Cellular Targets Of Plant Derived Aldehydes And Degradable Pro-Antimicrobial Networks In Pseudomonas Aeruginosa, Yetunde Adewunmi Dec 2019

The Antimicrobial Activity And Cellular Targets Of Plant Derived Aldehydes And Degradable Pro-Antimicrobial Networks In Pseudomonas Aeruginosa, Yetunde Adewunmi

Dissertations

Essential oils (EOs) are plant-derived products that have been long exploited for their antimicrobial activities in medicine, agriculture, and food preservation. EOs represent a promising alternative to conventional antibiotics due to the broad-range antimicrobial activity, low toxicity to human commensal bacteria, and the capacity to kill microorganisms without promoting resistance. Despite the progress in the understanding of the biological activity of EOs, many aspects of their mode of action remain inconclusive. The overarching aim of this work was to address these gaps by studying molecular interactions between antimicrobial plant aldehydes and the opportunistic human pathogen Pseudomonas aeruginosa. We initiated …


Gogo: An Improved Algorithm To Measure The Semantic Similarity Between Gene Ontology Terms, Chenguang Zhao May 2019

Gogo: An Improved Algorithm To Measure The Semantic Similarity Between Gene Ontology Terms, Chenguang Zhao

Master's Theses

Measuring the semantic similarity between Gene Ontology (GO) terms is an essential step in functional bioinformatics research. We implemented a software named GOGO for calculating the semantic similarity between GO terms. GOGO has the advantages of both information-content-based and hybrid methods, such as Resnik’s and Wang’s methods. Moreover, GOGO is relatively fast and does not need to calculate information content (IC) from a large gene annotation corpus but still has the advantage of using IC. This is achieved by considering the number of children nodes in the GO directed acyclic graphs when calculating the semantic contribution of an ancestor node …


Protein Residue-Residue Contact Prediction Using Stacked Denoising Autoencoders, Joseph Bailey Luttrell Iv Aug 2016

Protein Residue-Residue Contact Prediction Using Stacked Denoising Autoencoders, Joseph Bailey Luttrell Iv

Honors Theses

Protein residue-residue contact prediction is one of many areas of bioinformatics research that aims to assist researchers in the discovery of structural features of proteins. Predicting the existence of such structural features can provide a starting point for studying the tertiary structures of proteins. This has the potential to be useful in applications such as drug design where tertiary structure predictions may play an important role in approximating the interactions between drugs and their targets without expending the monetary resources necessary for preliminary experimentation. Here, four different methods involving deep learning, support vector machines (SVMs), and direct coupling analysis were …